SQL Performance Explained


Markus Winand - 2011
    The focus is on SQL-it covers all major SQL databases without getting lost in the details of any one specific product. Starting with the basics of indexing and the WHERE clause, SQL Performance Explained guides developers through all parts of an SQL statement and explains the pitfalls of object-relational mapping (ORM) tools like Hibernate. Topics covered include: Using multi-column indexes; Correctly applying SQL functions; Efficient use of LIKE queries; Optimizing join operations; Clustering data to improve performance; Pipelined execution of ORDER BY and GROUP BY; Getting the best performance for pagination queries; Understanding the scalability of databases. Its systematic structure makes SQL Performance Explained both a textbook and a reference manual that should be on every developer's bookshelf.

Hands-On Machine Learning with Scikit-Learn and TensorFlow


Aurélien Géron - 2017
    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

Absolute Freebsd: The Complete Guide to Freebsd


Michael W. Lucas - 2007
    But it can be even trickier to use than either Unix or Linux, and harder still to master.Absolute FreeBSD, 2nd Edition is your complete guide to FreeBSD, written by FreeBSD committer Michael W. Lucas. Lucas considers this completely revised and rewritten second edition of his landmark work to be his best work ever; a true product of his love for FreeBSD and the support of the FreeBSD community. Absolute FreeBSD, 2nd Edition covers installation, networking, security, network services, system performance, kernel tweaking, filesystems, SMP, upgrading, crash debugging, and much more, including coverage of how to:Use advanced security features like packet filtering, virtual machines, and host-based intrusion detection Build custom live FreeBSD CDs and bootable flash Manage network services and filesystems Use DNS and set up email, IMAP, web, and FTP services for both servers and clients Monitor your system with performance-testing and troubleshooting tools Run diskless systems Manage schedulers, remap shared libraries, and optimize your system for your hardware and your workload Build custom network appliances with embedded FreeBSD Implement redundant disks, even without special hardware Integrate FreeBSD-specific SNMP into your network management system. Whether you're just getting started with FreeBSD or you've been using it for years, you'll find this book to be the definitive guide to FreeBSD that you've been waiting for.

The Art of Readable Code


Dustin Boswell - 2010
    Over the past five years, authors Dustin Boswell and Trevor Foucher have analyzed hundreds of examples of "bad code" (much of it their own) to determine why they’re bad and how they could be improved. Their conclusion? You need to write code that minimizes the time it would take someone else to understand it—even if that someone else is you.This book focuses on basic principles and practical techniques you can apply every time you write code. Using easy-to-digest code examples from different languages, each chapter dives into a different aspect of coding, and demonstrates how you can make your code easy to understand.Simplify naming, commenting, and formatting with tips that apply to every line of codeRefine your program’s loops, logic, and variables to reduce complexity and confusionAttack problems at the function level, such as reorganizing blocks of code to do one task at a timeWrite effective test code that is thorough and concise—as well as readable"Being aware of how the code you create affects those who look at it later is an important part of developing software. The authors did a great job in taking you through the different aspects of this challenge, explaining the details with instructive examples." —Michael Hunger, passionate Software Developer

Successful Business Intelligence: Secrets to Making BI a Killer App


Cindi Howson - 2007
    Learn about the components of a BI architecture, how to choose the appropriate tools and technologies, and how to roll out a BI strategy throughout the organisation.

Introducing Microsoft Power BI


Alberto Ferrari - 2016
    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People


Aditya Y. Bhargava - 2015
    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

The Visual Display of Quantitative Information


Edward R. Tufte - 1983
    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Services


Brendan Burns - 2018
    Building these systems is complicated and, because few formally established patterns are available for designing them, most of these systems end up looking very unique. This practical guide shows you how to use existing software design patterns for designing and building reliable distributed applications.Although patterns such as those developed more than 20 years ago by the Gang of Four were largely restricted to running on single machines, author Brendan Burns--a Partner Architect in Microsoft Azure--demonstrates how you can reuse several of them in modern distributed applications.Systems engineers and application developers will learn how these patterns provide a common language and framework for dramatically increasing the quality of your system.

The Art of Doing Science and Engineering: Learning to Learn


Richard Hamming - 1996
    By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

Agile Estimating and Planning


Mike Cohn - 2005
    In this book, Agile Alliance cofounder Mike Cohn discusses the philosophy of agile estimating and planning and shows you exactly how to get the job done, with real-world examples and case studies.Concepts are clearly illustrated and readers are guided, step by step, toward how to answer the following questions: What will we build? How big will it be? When must it be done? How much can I really complete by then? You will first learn what makes a good plan-and then what makes it agile.Using the techniques in Agile Estimating and Planning , you can stay agile from start to finish, saving time, conserving resources, and accomplishing more. Highlights include:Why conventional prescriptive planning fails and why agile planning works How to estimate feature size using story points and ideal days--and when to use each How and when to re-estimate How to prioritize features using both financial and nonfinancial approaches How to split large features into smaller, more manageable ones How to plan iterations and predict your team's initial rate of progress How to schedule projects that have unusually high uncertainty or schedule-related risk How to estimate projects that will be worked on by multiple teams Agile Estimating and Planning supports any agile, semiagile, or iterative process, including Scrum, XP, Feature-Driven Development, Crystal, Adaptive Software Development, DSDM, Unified Process, and many more. It will be an indispensable resource for every development manager, team leader, and team member.

Operational Excellence Pillar: AWS Well-Architected Framework (AWS Whitepaper)


AWS Whitepapers - 2017
    It provides guidance to help you apply best practices in the design, delivery, and maintenance of AWS environments. This documentation is offered for free here as a Kindle book, or you can read it in PDF format at https://aws.amazon.com/whitepapers/.

Reactive Microservices Architecture


Jonas Bonér - 2016
    Specifically, you’ll learn how a Reactive microservice isolates everything (including failure), acts autonomously, does one thing well, owns state exclusively, embraces asynchronous message passing, and maintains mobility.Bonér also demonstrates how Reactive microservices communicate and collaborate with other services to solve problems. Get a copy of this exclusive report and find out how to bring your enterprise system into the 21st century.Jonas Bonér is Founder and CTO of Lightbend, inventor of the Akka project, co-author of the Reactive Manifesto and a Java Champion. Learn more at: http://jonasboner.com.

Fundamentals of Software Architecture: An Engineering Approach


Mark Richards - 2020
    Until now. This practical guide provides the first comprehensive overview of software architecture's many aspects. You'll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics.Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You'll focus on architecture principles with examples that apply across all technology stacks.

Programming Concurrency on the JVM


Venkat Subramaniam - 2011
    Speedy and affordable multicore hardware is driving the demand for high-performing applications, and you can leverage the Java platform to bring these applications to life. Concurrency on the Java platform has evolved, from the synchronization model of JDK to software transactional memory (STM) and actor-based concurrency. This book is the first to show you all these concurrency styles so you can compare and choose what works best for your applications. You'll learn the benefits of each of these models, when and how to use them, and what their limitations are. Through hands-on exercises, you'll learn how to avoid shared mutable state and how to write good, elegant, explicit synchronization-free programs so you can create easy and safe concurrent applications. The techniques you learn in this book will take you from dreading concurrency to mastering and enjoying it. Best of all, you can work with Java or a JVM language of your choice - Clojure, JRuby, Groovy, or Scala - to reap the growing power of multicore hardware. If you are a Java programmer, you'd need JDK 1.5 or later and the Akka 1.0 library. In addition, if you program in Scala, Clojure, Groovy or JRuby you'd need the latest version of your preferred language. Groovy programmers will also need GPars.